In order to make material design processes more efficient in the future, the underlying multidimensional process parameter spaces must be systematically explored using digitalisation techniques such as machine learning (ML) and digital simulation. In this paper we shortly review essential concepts for the digitalisation of electrodeposition processes with a special focus on chromium plating from trivalent electrolytes.
In this paper, we attempt to present a new approach and analytical relation between perimeter-to-area ratio (P/A) and the plated thickness using Variable Area Window (VAW) test mask for improved thickness estimation. Although, the approach is illustrated using selective plating of gold films by varying two dimensional patterned windows on metallised silicon surface as an example, yet the method can be applied to other cases also. The method includes selective electroplating of gold in rectangular and circular windows wherein P/A of patterned shapes (squares, rectangles and circles) has been varied from 0.001 cm-1 to 0.4 cm-1 i.e. a factor of 400, a range normally used for practical modern MEMS devices. Experiments show that in general the thickness increases with increasing P/A because of current crowding. However, in contrast to using current density for control of this current crowding as reported in literature, we report that by careful design of mask pattern and improved material parameters, one can control and even achieve a slope reversal in the plot of thickness vs. P/A. The increase in thickness as measured by slope of linear fit is about 3 µm/(P/A in µm-1) for sharp edges compared to about 0.8 µm/(P/A in µm-1) for curved edges within the experimental errors. The general applicability of these relations to practical cases is confirmed by analysing the previously reported trends of data from the literature on Ni films using similar patterned shapes.